NOMA系统中低复杂度的串行信号检测算法  

Low Complexity Successive Signal Detection Algorithm in NOMA System

作　　者：王歌 赵知劲[1] WANG Ge;ZHAO Zhi-jin(College of Telecommunication Engineering, Hangzhou Dianzi University, Hangzhou, Zhejiang 310018, China)

机构地区：[1]杭州电子科技大学通信工程学院,浙江杭州310018

出　　处：《信号处理》2019年第1期26-31,共6页Journal of Signal Processing

基　　金：国家自然科学基金(61571172)

摘　　要：在大规模天线情况下,针对现有的迫零串行干扰消除(ZF-SIC)算法和最小均方误差串行干扰消除(MMSE-SIC)算法中存在的高复杂度问题,提出了低复杂度的ND-ZF-SIC和ND-MMSE-SIC算法。首先利用对角矩阵分解将大矩阵分解为对角矩阵与空心矩阵之和。其次,利用诺伊曼级数近似,将大矩阵的直接求逆运算转化为对角矩阵求逆运算的乘积之和。为了在降低复杂度的同时保证近似的精度,采用诺伊曼级数的前两项进行近似。由于对角矩阵的求逆运算只需求对角线上元素的倒数,因此大大降低了算法复杂度。ZF-SIC、ND-ZF-SIC、MMSE-SIC和ND-MMSE-SIC算法的仿真结果表明,ND-ZF-SIC和ND-MMSE-SIC算法的误码率分别与ZF-SIC和MMSE-SIC相近。In the case of large-scale antennas, there are high complexity problems in the existing zero forcing successive interference cancellation (ZF-SIC) algorithm and the minimum mean square error successive interference cancellation (MMSE-SIC) algorithm. In order to solve this problem, low complexity ND-ZF-SIC algorithm and ND-MMSE-SIC algorithm are proposed. First, the diagonal matrix decomposition is used to decompose the large matrix into the sum of the diagonal matrix and the hollow matrix. Secondly, the Neumann series approximation is used to convert the direct inversion of the large matrix into the sum of the products of the diagonal matrix inversion. In order to reduce the complexity while ensuring the accuracy of the approximation, the first two terms of the Neumann series are taken. Since the inverse of the diagonal matrix only requires the reciprocal of the elements on the diagonal, ND-ZF-SIC and ND-MMSE-SIC greatly reduce the complexity of the original algorithm. The simulation results of ZF-SIC, ND-ZF-SIC, MMSE-SIC and ND-MMSE-SIC show that the error bit performance of ND-ZF-SIC and ND-MMSE-SIC is similar to ZF-SIC and MMSE-SIC, respectively.

关 键 词：第五代移动通信 非正交多址接入 诺伊曼级数近似 对角矩阵分解 

分 类 号：TN929.5[电子电信—通信与信息系统]